Stress in the NHS: why the UK pharmacy industry needs to embrace data

The well-publicised stresses affecting the NHS are clearly already impacting the retail pharmacy ecosystem.

Market volatility is accelerating consolidation, causing changes to chain ownership, and influencing brand strategies and commercial priorities. In July 2022, over 3,000 (31%) pharmacies in England experienced unplanned closures due to staff shortages, representing 12,455 lost hours of community health management  . In January 2023, Lloyds Pharmacies announced it will be closing all 273 of its in-store Sainsbury’s outlets, and in June Boots announced 300 store closures.

Less access to local GP services is changing the footfall and profitability of many retail pharmacies and predictability is becoming an issue. Both pharmacy and pharmaceutical distribution are low margin business models and the ability to absorb uncertainty and risk is limited. For pharmacy owners, it is essential to understand the changing dynamics of the local population, and for pharmaceutical distributors, the ability to understand how these changes impact inventory and logistics operations is vital.

The patient population is also evolving as these stresses manifest across the country. As access to healthcare continues to be a problem, and as community pharmacy infrastructure moves, closes or changes ownership, the needs, behaviours and beliefs of patients will create new patterns in footfall. There is a strong possibility that previously brand-loyal customers will migrate to new or different pharmacies as a result. Will Boots and Lloyds continue to be the dominant players, will their customer offering remain the same or change, and most importantly will customers remain loyal as their business model evolves?

These changes all impact established perceptions of demand and distribution need and, if understood, also facilitate investment decisions for chain owners and new pharmacy investors.

With this much stress in the market, the established norms that your capabilities are built around have already evolved. Disruption always presents opportunity for those primed to exploit it – and data is the perfect tool to realise that opportunity.

Demand management and purchasing/replenishment needs to be flexible. It also needs to be anticipatory: what is happening to my patient population today and what does this mean for my ordering tomorrow? What types of service and terms do I need to maintain (or grow) my profitability? Are my perceptions of loyalty (to a distributor) based on today’s business reality or yesterday’s more stable environment? If you are a distributor, are your customers purchasing needs and behaviours changing, and is your business model flexible enough to capitalise on emerging opportunities as well as mitigate risk? In a period of ownership change, what are your competitors doing differently and why? Are you immune to significant ownership and structural changes to long established retail pharmacy chains if they occur?

For both pharmacies and distributors the core challenge of optimised inventories, locations of these inventories and the timing of replenishment activities is more crucial than ever. Optimising the balance sheet whilst driving the P&L is critical to cash flow and profitability – again, in a low margin business, is it sensible to continue managing your inventory needs based on old assumptions, or should you be investing in data competency as an enabler of performance optimisation?

In our experience, pharmaceutical manufacturers, drugs distributors and pharmacies generate a wealth of data across drug prescribing, purchasing, supply & demand and other inputs, and have done so over many decades of operation. This data is often used primarily for basic operational decision support (trending, demand, purchasing etc), management and financial reporting. Our observation is that, compared to other industry segments, analysis of the available data is not focused enough on insight generation or behavioural levers. As a result, opportunities to extract value are missed.

Utilising data science and machine learning in retail pharmacy and distribution will move your understating of the UK market from, “what just happened, and what can I learn from it?” into, “I can anticipate my customer/patients’ needs, and what I need to do differently to succeed”.

In a market where margin from the buy and sell model is eroding, isn’t it time to at least explore the power of your data to create enhanced or even new revenue streams?

At a time when so many questions are being asked about access, critical medicine supply, post pandemic population behaviours and more, do you really understand how powerful your data capabilities could be, and how they could benefit your customers better? The proactive development of an enterprise-wide data strategy to inform how to transform patient care and improve patient outcomes is not a core competency for you today, but it carries the potential to revolutionise your business tomorrow.

There are several key considerations for drugs distributors and pharmacy brands given the anticipated changes to the UK landscape. Data science will generate insights to enable you to:
1. Create flexible and anticipatory supply chains, minimising inventory holdings whilst increasing patient-facing supply.

2. Generate hyper-local insights into your locality and its population. Across pharmacy chains local populations will have varying needs and priorities – understanding each local community will ensure optimised and differentiated offerings by outlet.

3. Identify mutually beneficial service level models (pharmacy and distributor). Eliminate wastage, reduce mileage and enhance operating margins.

4. Establish network optimisation. Is your real estate in the correct locations, how does your inventory flow through your network, where are bottlenecks or supply black spots created (and why)?

5. De-risk investment in service strategies. Identify opportunities for higher rates of return through service provision based on your captive patient population.

6. Manage inventory shortages more efficiently. Match supply with need based on better insights.

7. Understand brand building opportunities based on population need. Does your community want/need the ‘supermarket’ experience, or does it respond to a more bespoke/intimate experience?

8. Scenario planning and insights for pharmacy– what happens if your local Lloyds shops changes hands or if Boots closes its nearest high street shop? What opportunities and threats can you anticipate, and how do you react to them?

9. Scenario and planning insights for distributors – what happens to your efficiency if chains radically transform/contract/disappear? What knock on effects does this have on service level delivery to other pharmacy outlets and chains?

Evolving your own capabilities using easily accessible data management innovation carries many potential benefits. Many new data streams are ‘free’ to access, so the investment focus should be on how you manage the available data, not how much you spend on it. Data purchase costs can be reduced by having less reliance on traditional data sets through augmentation with more behaviourally focussed inputs.

Machine learning speeds up the process exponentially, allowing greater industrialisation of vast amounts of data. Your decision-making process can be better informed, carry enhanced scenario capabilities, and options can be visible to you in near real time. This ability to manage complexity can build a ‘one version of the truth’ model for your entire internal enterprise, linking your brand with demand, logistics, purchasing, finance and quality like never before.

Most importantly, your enhanced ability to use data will generate new value insights and levers. Your relationships with customers and patients can, and will, change as a result. Service levels, inventory positions, frequency of supply and service orientation will be based on a depth and granularity of data previously unavailable through traditional models. Your patients benefit, your customers will experience higher ROI, and your brand(s) will flourish.

Artefact is a global data services company helping organisations transform data into value and business impact. We translate client challenges into tangible results using digital, data and AI.

Artefact’s Healthcare AI platform predicts detailed information on the market demand for drugs and demographic factors. We have the most comprehensive pharmaceutical distribution data in the UK through aggregating market available data, from NHS prescriptions to local demographics. We further boost the powers of the platform by enhancing it with our client’s data, to adapt predictions to your organisation’s continuously evolving business environment. As a result, our Healthcare AI platform leads to patient outcome improvements by driving targeted actions through dozens of use cases, each designed to support the most critical business processes, from supply chain optimisation to product portfolio management.

Artefact are convinced by the power of data to transform the UK healthcare model and the need for disruption is now. Reach out to us to discuss how we can help you unlock new insights and transform your business operations through data.